Granted, there’s still plenty of time left in the NCAA tournament (and a number of games to lose), but after last night’s Sweet 16 matchups, this writer finds himself in first place in one large competitive bracket and two points out of first place in another. In both cases, the brackets are at or near the top in terms of possible remaining points. I wish I could tell you this was the result of some magnificent accumulation of college basketball wisdom or hours upon hours of diligent bracket study. In reality, it’s no exaggeration to say that I’ve not watched one entire college basketball game this entire season, perhaps not even one complete half. Embarrassingly, I’ve listened to several of the better tourney games driving in the car and had to pay very close attention to the team possession information because none of the players’ names ring a bell. I’m so ill informed that I become confused and tune out.
How could this happen? Instead of poring over bracket decisions, I decided to blindly follow the bracket recommended by a leading statistical expert, who used several relatively simple inputs to develop probabilities for each game, start to finish. My brackets took me less than five minutes to fill out. The past several years prior, I used a different statistical model to fill out brackets with similar solid results. These past brackets were filled out quickly, the morning of the first games. I’ve never won, and I probably won’t win this year due to randomness and dumb luck, but I’ve always been smack-dab in the running the final week and finished near the top. Separately, over the past seven or eight fall college football seasons, I’ve participated in a running weekly pick-em pool that involves roughly 25 games per week over the course of the entire season. Beginning year before last, I abandoned qualitative judgment and picked solely on a publicly available statistical model. Each week, I purposefully ignore all qualitative information and pick solely based upon the model, no matter how badly my brain wants to change some of the answers. The results: a first place finish the first year and a third place finish this past year.
What does this have to do with value investing? A bunch, actually, in our opinion. In past blog posts, we’ve talked about the “fundamental free lunches” available in the equities market place. Simply, we’ve shown that buying individual stocks year over year that are bottom of the barrel in terms of quantitative valuation according to several simple fundamental metrics leads to statistically significant long-term outperformance. You literally didn’t need to know one thing about any of the stocks picked through the years to achieve the outperformance over the long run. Actually, in most cases, the stocks picked would have caused the rational part of your brain to go entirely haywire. By nature, many true value stocks have fallen out of favor for one reason or another, whether management problems, fraud, secular industry decline, or product issues. Yet, time and time again, a number of these names eventually revert back to the mean generating solid returns. On the flip side, the highflying names that are usually showing up on the front covers of the daily business papers and weekly magazines are overvalued and prone to revert downward over time.
Like the NCAA bracket and college football examples above, the value investing process is ultimately a probability issue. Our simple examples in past blog posts and a bunch of academic research shows that if you pick bottom decile stocks valuation-wise, for instance, the odds work in your favor that portfolio performance will come in above the averages over longer time periods. Unfortunately, the human brain is subject to a number of biases that lead us to make a bunch of regrettable decisions. In the bracket examples above, objectively picking using the statistical model eliminates the biases we have from a number of different directions, such as tendencies to pick traditional powerhouse teams, or to favor teams from a certain conference or geographical region, or that have a star player we really like. In the stock-picking world, similar qualitative biases lead us to shun the cheap companies and chase the overvalued. Our brains tell us to avoid the undervalued because the management team is in turmoil perhaps, or because the last product was an absolute flop. Meanwhile, we buy because the CEO is on the cover of Forbes, or because their particular widget is the darling of the tech or retail world. Doing so leads to substandard returns. Several studies, for instance show that retail and institutional investors generally have an awful market-timing track record, buying wholeheartedly at market peaks and selling hand over fist at market bottoms.
There are caveats, however, to taking objective approaches.
- First, you need to find the right metrics or models. In the investing world, we know that certain fundamental multiples like price to book and EV/EBITDA are far better long-term performance predictors than metrics such as forward P/E ratios. In our NCAA bracket and football examples above, we used models that have been developed over long periods of time. A tourney bracket based upon the relative positions of the moon and stars in the sky at various points during the tourney probably wouldn’t get you very far. Keep in mind, it’s important not choosing metrics or models because they tell you what you want to hear all the time.
- Second, you have to commit yourself to the process and maintain discipline, no matter how bad it hurts. In value investing, it’s easy to come up with a million different reasons why a certain company’s stock shouldn’t get consideration. There are ways to mitigate this anxiety. For instance, one can employ risk management rules or technical analysis to ensure that a particular name doesn’t harm performance in an outsized way. Nonetheless, even with risk procedures in place, it’s very difficult mentally to get involved in names that aren’t necessarily belles of the stock-picking ball. Likewise, in clicking the teams for my bracket, rest assured there were many tempting overrides.
- Third, and perhaps most important, one has to understand that taking probabilistic approaches doesn’t guarantee you win every time period. Patience is absolutely a key part. Consistency becomes more important than shooting the lights out. In markets, sometimes value is in favor, sometimes it isn’t. In past blog posts, we showed several year stretches where certain fundamental metrics underperformed only to come back with a vengeance on the upside. Many investors lose patience with a process due to a stretch of underperformance and abandon the process at precisely the wrong moment instead. Our “humanness” gets in the way. Take the football pool. On the way to those first and third place finishes, this writer rarely won the weekly intervals outright. However, rarely were the picks at the very bottom of the pool in any given week. Surely, a few weeks were stinkers, but the odds eventually won out over the course of 14 weeks. Grind-it-out consistency is the central idea, not too dissimilar to the tortoise vs. hare example.
We’ll see how the rest of the tourney plays out. Whether the bracket finishes first or not, we know it’s been a good run. Plus, we’ll know the outcome one-way or the other within a week! Markets, however, test patience, consistency, and discipline over years and decades. Academics and investors have asked repeatedly how efficient or moderately efficient markets can continue to offer a value premium over long periods of time. Perhaps it’s best summed up in quote attributed to John Maynard Keynes: “Markets can remain irrational a lot longer than you and I can remain solvent.”
